Leaf area index estimation using top-of-canopy airborne RGB images

叶面积指数 天蓬 遥感 生长季节 树冠 环境科学 地理 数学 农学 生物 考古
作者
Rahul Raj,Jeffrey P. Walker,Rohit Pingale,Rohit Nandan,Balaji Naik,J. Adinarayana
出处
期刊:International journal of applied earth observation and geoinformation 卷期号:96: 102282-102282 被引量:68
标识
DOI:10.1016/j.jag.2020.102282
摘要

Leaf Area Index (LAI) is one of the most important biophysical properties of a crop, used in detecting long-term water stress, estimating biomass, and identifying crop growth stage. Remote sensing based LAI estimation techniques perform well for early growth stages but tend to produce high error during the crop reproductive stage due to canopy closure. Moreover, estimation of the true LAI from individual leaf measurements remains a challenge. Consequently, two alternate methods have been developed and compared for estimating the LAI of a maize crop using top-of-canopy RGB images collected throughout the growing season using a hexacopter. Both methods used the RGB images to estimate the canopy height and the green-canopy cover together with a 'vertical leaf area distribution factor' (VLADF) from allometric relations (using crop height from RBG images and days after sowing). The first method used an empirical approach to estimate the LAI from training a linear function of the above inputs to Licor canopy analyser values of LAI. The method was trialled for a research farm located in a semi-arid area of southern peninsula India and found to have validation results with an R2 of 0.84 and RMSE of 0.36 for the unused portion of the Rabi (post-monsoon) season data of 2018–19, and R2 of 0.77 and RMSE of 0.45 for the Rabi 2019–20 season data when compared with Licor LAI values. While seemingly acceptable, the Licor canopy analyser gives a foliage area index and so the accuracy of this model was very low (R2 of 0.56 and RMSE of 1.34) when evaluated with true LAI from manual measurements of the leaf area. Consequently, a refinement was introduced using only VLADF, green-canopy cover estimates from the RBG images, and a field measured top leaf angle. The output derived from this conceptual model had an R2 of ~0.6 and RMSE of 0.73 when compared with the true LAI values. Importantly, the LAI from this conceptual model was found to be unaffected by canopy closure during the reproductive stage of the crop.
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